Combining Genome-Wide Association Study and Gene-Based Haplotype Analysis to Identify Candidate Genes for Alkali Tolerance at the Germination Stage in Rice

Abstract

Salinity–alkalinity stress is one of the main abiotic factors limiting rice production worldwide. With the widespread use of rice direct seeding technology, it has become increasingly important to improve the tolerance to salinity–alkalinity of rice varieties at the germination stage. Although we have a more comprehensive understanding of salt tolerance in rice, the genetic basis of alkali tolerance in rice is still poorly understood. In this study, we measured seven germination-related traits under alkali stress and control conditions using 428 diverse rice accessions. The alkali tolerance levels of rice germplasms varied considerably during germination. Xian/indica accessions had generally higher tolerance to alkali stress than Geng/japonica accessions at the germination stage. Using genome-wide association analysis, 90 loci were identified as significantly associated with alkali tolerance. Eight genes (LOC_Os01g12000, LOC_Os03g60240, LOC_Os03g08960, LOC_Os04g41410, LOC_Os09g25060, LOC_Os11g35350, LOC_Os12g09350, and LOC_Os12g13300) were selected as important candidate genes for alkali tolerance based on the gene functional annotation and gene-CDS-haplotype analysis. According to the expression levels of LOC_Os09g25060 (OsWRKY76), it is likely to play a negative regulatory role in alkali tolerance during rice germination. An effective strategy for improving rice alkali tolerance may be to pyramid alkali-tolerant haplotypes of multiple candidate genes to obtain the optimal haplotype combination. Our findings may provide valuable genetic information and expand the use of alkali tolerance germplasm resources in rice molecular breeding to improve the alkali tolerance at the germination stage.

Genome‐wide association studies for rice seed germination under drought stress using 3VmrMLM

“…Indica accessions showed faster germination under drought stress compared to Japonica accessions. This finding was consistent with previous researches which highlighted that Indica subpopulations presented higher seed vigor than Japonica under normal or stress conditions (Dai et al., 2022; Du et al., 2023; Li et al., 2021; Mei et al., 2022; Wang et al., 2010). The wide range of phenotypic variation suggested that these accessions have a diverse genetic background and are suitable for studying the genetic architecture of drought tolerance during seed germination.…”

Genetic Dissection of Alkalinity Tolerance at the Seedling Stage in Rice (Oryza sativa) Using a High-Resolution Linkage Map

“…Alkaline stress is more complicated than saline stress and deciphering the mechanisms of alkalinity tolerance at the seedling stage of rice is critical for improving rice production. Although several QTLs and candidate genes for alkalinity tolerance have been identified in rice [ 6 , 30 , 33 , 34 , 35 , 36 , 41 , 42 ], the molecular mechanism of alkalinity tolerance at the seedling stage in rice is not yet elucidated in greater detail. Thus, there is a need to unravel the molecular mechanisms and candidate genes associated with alkalinity tolerance in rice.…”

Genome-wide association studies identified OsTMF as a gene regulating rice seed germination under salt stress

“…The general linear model (GLM) with the first three principal components matrix calculated from genotypes was employed using Tassel 5.2.54 software ( Bradbury et al., 2007 ) to perform GWAS for seed germination under salt stress. Across the whole panel of varieties, 302,900 high-quality SNPs were used for GWAS after removing SNPs with missing rates of more than 20% and minor allele frequencies of less than 5% ( Ju et al., 2022 ; Mei et al., 2022 ). To identify significant SNPs, the Bonferroni correction method was used to calculate suggestive significance thresholds of associations, resulting in a p value of 1.65 × 10 -7 (0.05/N, with N = number of SNPs) ( Shi et al., 2017 ).…”

“…Functional annotations for genes within genomic regions of interest were obtained in reference to the Nipponbare genome IRGSP 1.0 ( Kawahara et al., 2013 ). Haplotype analyses were performed using SNPs in the coding sequences, with each haplotype possessing at least twenty rice varieties ( Mei et al., 2022 ).…”